code: def find_step_scaler_on_hexagon_grid(grid, center=None, std=1):
      """
      Find step scale for neighbouring neurons. The further
      neuron from the center the lower step scale it has.
  
      Notes
      -----
      Non-neighbor neurons will have high step size
      We do not set up it to zero, since later we will
      ignore these values anyway
  
      Parameters
      ----------
      grid : array-like
  
      center : object
          Variable is going to be ignored. It's defined
          only for compatibility with other functions
  
      {find_step_scaler_on_rect_grid.std}
      """
      return gaussian_df(grid, mean=1, std=std)
  
file_path: neupy/neupy/algorithms/competitive/neighbours.py
imports: from __future__ import division
  import numpy
  from neupy.core.docs import shared_docs
label_desc: Use image node_id 7 for calling a global function with example usage: find_step_scaler_on_hexagon_grid(grid, center, std) and returns: gaussian_df